Recognition of handwritten Chinese characters via short line segments
Identifieur interne : 000623 ( Istex/Corpus ); précédent : 000622; suivant : 000624Recognition of handwritten Chinese characters via short line segments
Auteurs : Hsi-Jian Lee ; Bin ChenSource :
- Pattern Recognition [ 0031-3203 ] ; 1991.
Abstract
A system to recognize handwritten Chinese characters is presented. In the first stage, short line segments are extracted, where a new efficient algorithm is proposed, based on accumulated chain codes, for line approximation. In the feature extraction stage, features of each character are computed, which are further defined by the features of its composing line segments. In the matching stage, dynamic programming is first used to calculate the similarity between a segment of the input character and a segment of the reference character, and then the similarity between the two characters is computed. In order to reduce the number of candidates, a coarse classification algorithm is proposed. The recognition rate for 150 characters is about 90%, excluding the error in coarse classification.
Url:
DOI: 10.1016/0031-3203(92)90052-K
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In the first stage, short line segments are extracted, where a new efficient algorithm is proposed, based on accumulated chain codes, for line approximation. In the feature extraction stage, features of each character are computed, which are further defined by the features of its composing line segments. In the matching stage, dynamic programming is first used to calculate the similarity between a segment of the input character and a segment of the reference character, and then the similarity between the two characters is computed. In order to reduce the number of candidates, a coarse classification algorithm is proposed. 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In the first stage, short line segments are extracted, where a new efficient algorithm is proposed, based on accumulated chain codes, for line approximation. In the feature extraction stage, features of each character are computed, which are further defined by the features of its composing line segments. In the matching stage, dynamic programming is first used to calculate the similarity between a segment of the input character and a segment of the reference character, and then the similarity between the two characters is computed. In order to reduce the number of candidates, a coarse classification algorithm is proposed. 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In the first stage, short line segments are extracted, where a new efficient algorithm is proposed, based on accumulated chain codes, for line approximation. In the feature extraction stage, features of each character are computed, which are further defined by the features of its composing line segments. In the matching stage, dynamic programming is first used to calculate the similarity between a segment of the input character and a segment of the reference character, and then the similarity between the two characters is computed. In order to reduce the number of candidates, a coarse classification algorithm is proposed. The recognition rate for 150 characters is about 90%, excluding the error in coarse classification.</abstract><subject><genre>Keywords</genre><topic>Structural matching</topic><topic>Dynamic programming</topic><topic>Thinning</topic><topic>Line approximation</topic><topic>Optical character recognition</topic></subject><relatedItem type="host"><titleInfo><title>Pattern Recognition</title></titleInfo><titleInfo type="abbreviated"><title>PR</title></titleInfo><genre type="Journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">199205</dateIssued></originInfo><identifier type="ISSN">0031-3203</identifier><identifier type="PII">S0031-3203(00)X0212-9</identifier><part><date>199205</date><detail type="volume"><number>25</number><caption>vol.</caption></detail><detail type="issue"><number>5</number><caption>no.</caption></detail><extent unit="issue pages"><start>445</start><end>553</end></extent><extent unit="pages"><start>543</start><end>552</end></extent></part></relatedItem><identifier type="istex">7EB1553EBE0C463E68131E0D8AFE470AC6E5D890</identifier><identifier type="DOI">10.1016/0031-3203(92)90052-K</identifier><identifier type="PII">0031-3203(92)90052-K</identifier><recordInfo><recordContentSource>ELSEVIER</recordContentSource></recordInfo></mods></metadata><enrichments><istex:catWosTEI uri="https://api.istex.fr/document/7EB1553EBE0C463E68131E0D8AFE470AC6E5D890/enrichments/catWos"><teiHeader><profileDesc><textClass><classCode scheme="WOS">COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE</classCode><classCode scheme="WOS">ENGINEERING, ELECTRICAL & ELECTRONIC</classCode></textClass></profileDesc></teiHeader></istex:catWosTEI></enrichments></istex></record>Pour manipuler ce document sous Unix (Dilib)
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